Vehicle Sideslip Angle Research Articles

Coordinated control of stability and economy based on torque distribution of distributed drive electric vehicle

The torque distribution strategy of distributed drive electric vehicle is only aimed at safety or economy. A multi-target coordinated control method considering stability and economy is proposed to solve the problem of single torque distribution target, which consists of a coordination decision controller, a high-level motion controller, and a low-level allocation controller. The coordination decision controller based on the phase plane method determines whether to adopt a stability or economic control strategy. The high-level motion controller consists of a bicycle model with 2 degree of freedom, a speed tracking controller, a stability controller, and an economic controller to calculate the desired direct yaw moment of the four in-wheel motors. The stability controller based on the fuzzy algorithm tracks the desired vehicle side slip angle and yaw rate calculated by the bicycle model with 2 degree of freedom to control vehicle stability. The economical controller based on a multi-motor loss model optimizes the efficiency of the vehicle’s drive system. The low-level allocation controller is presented to provide optimally distributed torques for each wheel. Finally, the simulation and hardware-in-the-loop testing show that the coordinated control strategy can effectively improve the stability and economy of the distributed drive electric vehicle.

Performance comparison of electric-vehicle drivetrain architectures from a vehicle dynamics perspective

Recent electric vehicle studies in literature utilize electric motors within an anti-lock braking system, traction-control system, and/or vehicle-stability controller scheme. Electric motors are used as hub motors, on-board motors, or axle motors prior to the differential. This has led to the need for comparing these different drivetrain architectures with each other from a vehicle dynamics standpoint. With this background in place, using MATLAB simulations, these three drivetrain architectures are compared with each other in this study. In anti-lock braking system and vehicle-stability controller simulations, different control approaches are utilized to blend the electric motor torque with hydraulic brake torque; motor ABS, torque decomposition, and optimal slip-tracking control strategies. The results for the anti-lock braking system simulations can be summarized as follows: (1) Motor ABS strategy improves the stopping distance compared to the standard anti-lock braking system. (2) In case the motors are not solely capable of providing the required braking torque, torque decomposition strategy becomes a good solution. (3) Optimal slip-tracking control strategy improves the stopping distance remarkably compared to the standard anti-lock braking system, motor anti-lock braking system, and torque decomposition strategies for all architectures. The vehicle-stability controller simulation results can be summarized as follows: (1) higher affective wheel inertia of the on-board and hub motor architecture dictates a higher need of wheel torque in order to generate the tire force required for the desired yaw rate tracking. A higher level of torque causes a higher level of tire slip. (2) Optimal slip-tracking control strategy reduces the tire slip trends drastically and distributes the traction/braking action to each tire with the control-allocation algorithm specifying the reference slip values. This reduces reference tire slip-tracking error and reduces vehicle sideslip angle. (3) Tire slip trends are lower with the hub motor architecture, compared to the other architectures, due to more precise slip control.

An Adaptive Approach to Real-Time Estimation of Vehicle Sideslip, Road Bank Angles, and Sensor Bias

Robust estimation of vehicle sideslip angle is essential for stability control applications. However, the direct measurement of sideslip angle is expensive for production vehicles. This paper presents a novel sideslip estimation algorithm which relies only on sensors available on passenger and commercial vehicles. The proposed method uses both kinematics and dynamics vehicle models to construct extended Kalman filter observers. The estimate relies on the results provided from the dynamics model observer where the tire cornering stiffness parameters are updated using the information provided from the kinematics model observer. The stability property of the proposed algorithm is discussed and proven. Finally, multiple experimental tests are conducted to verify its performance in practice. The results show that the proposed approach provides smooth and accurate sideslip angle estimation. In addition, our novel algorithm provides reliable estimates of bank angles and lateral acceleration sensor bias.

Virtual sensor for real-time estimation of the vehicle sideslip angle

Purpose The vehicle sideslip angle is an important state of vehicle lateral dynamics and its knowledge is crucial for the successful implementation of advanced driver-assistance systems. Measuring the vehicle sideslip angle on a production vehicle is challenging because of the exorbitant price of a physical sensor. This paper aims to present a novel framework for virtually sensing/estimating the vehicle sideslip angle. The desired level of accuracy for the estimator is to be within +/− 0.2 degree of the actual sideslip angle of the vehicle. This will make the precision of the proposed estimator at par with expensive commercially available sensors used for physically measuring the vehicle sideslip angle. Design/methodology/approach The proposed estimator uses an adaptive tire model in conjunction with a model-based observer. The performance of the estimator is evaluated through experimental tests on a rear-wheel drive vehicle. Findings Detailed experimental results show that the developed system can reliably estimate the vehicle sideslip angle during both steady state and transient maneuvers, within the desired accuracy levels. Originality/value This paper presents a novel framework for vehicle sideslip angle estimation. The presented framework combines an adaptive tire model, an unscented Kalman filter-based axle force observer and data from tire mounted sensors. Tire model adaptation is achieved by making extensions to the magic formula, by accounting for variations in the tire inflation pressure, load, tread-depth and temperature. Predictions with the adapted tire model were validated by running experiments on the Flat-Trac® machine. The benefits of using an adaptive tire model for sideslip angle estimation are demonstrated through experimental tests. The performance of the observer is satisfactory, in both transient and steady state maneuvers. Future work will focus on measuring tire slip angle and road friction information using tire mounted sensors and using that information to further enhance the robustness of the vehicle sideslip angle observer.

Design of an Interacting Multiple Model-Cubature Kalman Filter Approach for Vehicle Sideslip Angle and Tire Forces Estimation

Vehicle states estimation (e.g., vehicle sideslip angle and tire force) is a key factor for vehicle stability control. However, the accurate values of these parameters could not be obtained directly. In this paper, an interacting multiple model-cubature Kalman filter (IMM-CKF) is used to estimate the vehicle state parameters. And improvements about estimation method are achieved in this paper. Firstly, the accuracy of the reference model is improved by building two different models: one is 7-degree-of-freedom (7 DOF) vehicle model with linear tire model, and the other is 7 DOF vehicle model with nonlinear Dugoff tire model. Secondly, the different models are switched by IMM-CKF to match different driving condition. Thirdly, the lateral acceleration correction for sideslip angle estimation is considered, because the sensor of lateral acceleration is easy to be influenced by the gravity on banked road. Then, to compare cubature Kalman filter (CKF) estimation method and IMM-CKF estimation method Hardware-In-Loop (HIL) tests are carried out in the paper. And simulation results show that IMM-CKF methodology can provide accurate estimation values of vehicle states parameters.

Development and evaluation of torque distribution methods for four-wheel independent-drive electric vehicle based on parameter estimation

A hierarchical controller including a vehicle condition parameter estimator for improving the vehicle stability is theoretically applied to a four-wheel independent-drive electric vehicle. This study is aimed at combining the parameters estimation with vehicle stability control and evaluating different optimization algorithms based on the computation time and fluctuation. The hierarchical controller consists of a vehicle condition parameter estimator, active yaw moment controller, and torque distribution controller. The vehicle condition parameter estimator is based on the Unscented Kalman Filter, which avoids the truncation error caused by Taylor expansion to convert a nonlinear system into a linear system. The active yaw moment controller is designed based on the sliding mode control. The controller employs co-control between the vehicle sideslip angle and yaw rate, which properly accounts for both factors. The objective function of the torque distribution controller is based on the tire utilization function and constraint condition. The torque distribution and wheel slip rate are accounted for simultaneously. The torque distribution methods are tested based on nonlinear programming, quadratic programming, and weighted least squares for the sake of comparison. The simulation results demonstrate the accuracy of the proposed vehicle state estimator and the effectiveness of the proposed stability controller.

Tire Ply-Steer, Conicity and Rolling Resistance - Analytical Formulae for Accurate Assessment of Vehicle Performance during Straight Running

<div class="section abstract"><div class="htmlview paragraph">The aim of the paper is to provide simple and accurate analytical formulae describing the <i>straight motion</i> of a road vehicle. Such formulae can be used to compute either the steering torque or the additional rolling resistance induced by vehicle side-slip angle.</div><div class="htmlview paragraph">The paper introduces a revised formulation of the Handling Diagram Theory to take into account tire ply-steer, conicity and road banking. Pacejka’s Handling Diagram Theory is based on a relatively simple fully non-linear single track model. We will refer to the linear part of the Handling Diagram, since straight motion will be considered only. Both the elastokinematics of suspension system and tire characteristics are taken into account.</div><div class="htmlview paragraph">The validation of the analytical expressions has been performed both theoretically and after a subjective-objective test campaign.</div><div class="htmlview paragraph">By means of the new and unreferenced analytical formulae, practical hints are given to set to zero the steering torque during straight running. Additionally, the vehicle rolling resistance during straight motion is studied. It is found that front toe seems primarily set for reasons that are related to the steering system, other than tires. Reducing front toe could reduce energy consumption up to 1% on a WLTP mission.</div></div>

Event Data Recorder Performance during High Speed Yaw Testing Subsequent to a Simulated Tire Tread Separation Event

<div class="section abstract"><div class="htmlview paragraph">This paper presents event data from the Sensing and Diagnostic Module (SDM) of a 2004 Chevrolet Malibu during high speed yaw testing. Yaw tests were performed using tires that were intact and tires that had the tread removed. The tires that had the tread removed were placed at various wheel positions on the vehicle (e.g. leading side - front, leading side -rear, trailing side - rear). This testing simulates the loss of control phase subsequent to a tread separation. Speeds up to 117 km/h (72.9 mph) were achieved. A simple electro-mechanical device was incorporated to the dynamic testing to simulate a low-severity non-deployment event that triggered the recording of pre-crash data by the SDM. The SDM data from the tests was imaged and compared to reference data from vehicle-mounted instrumentation recording wheel speed, steering angle, measured vehicle sideslip angle and GPS calculated over the ground speed. This paper examines the dynamic effect of high sideslip angles and changes to tire rolling radius, as a result of a tread separation, as it pertains to the accuracy of EDR reported vehicle speed.</div></div>

Vehicle Sideslip Angle Estimation Based on Tire Model Adaptation

Information about the vehicle sideslip angle is crucial for the successful implementation of advanced stability control systems. In production vehicles, sideslip angle is difficult to measure within the desired accuracy level because of high costs and other associated impracticalities. This paper presents a novel framework for estimation of the vehicle sideslip angle. The proposed algorithm utilizes an adaptive tire model in conjunction with a model-based observer. The proposed adaptive tire model is capable of coping with changes to the tire operating conditions. More specifically, extensions have been made to Pacejka’s Magic Formula expressions for the tire cornering stiffness and peak grip level. These model extensions account for variations in the tire inflation pressure, load, tread depth and temperature. The vehicle sideslip estimation algorithm is evaluated through experimental tests done on a rear wheel drive (RWD) vehicle. Detailed experimental results show that the developed system can reliably estimate the vehicle sideslip angle during both steady state and transient maneuvers.

A direct yaw moment controller for a four in-wheel motor drive electric vehicle using adaptive sliding mode control

In this paper, a direct yaw moment control algorithm is designed such that the corrective yaw moment is generated through direct control of driving and braking torques of four in-wheel brushless direct current motors located at the empty space of vehicle wheels. The proposed control system consists of a higher-level controller and a lower-level controller. In the upper level of proposed controller, a PID controller is designed to keep longitudinal velocity constant in manoeuvres. In addition, due to probable modelling error and parametric uncertainties as well as adaptation of unknown parameters in control law, an adaptive sliding mode control through adaptation of unknown parameters is presented to yield the corrective yaw moment such that the yaw rate tracks the desired value and the vehicle sideslip angle maintains limited so as to improve vehicle handling stability. The lower-level controller allocates the achieved control efforts (i.e. total longitudinal force and corrective yaw moment) to driving or regenerative braking torques of four in-wheel motors so as to generate the desired tyre longitudinal forces. The additional yaw moment applied by upper-lever controller may saturate the tyre forces. To this end, a novel longitudinal slip ratio controller which is designed based on fuzzy logic is included in the lower-level controller. A tyre dynamic weight transfer-based torque distribution algorithm is employed to distribute the motor driving torque or regenerative braking torque of each in-wheel motor for vehicle stability enhancement. A seven degree-of-freedom non-linear vehicle model with Magic Formula tyre model as well as the proposed control algorithm are simulated in Matlab/Simulink software. Three steering inputs including lane change, double lane change and step-steer manoeuvres in different roads are investigated in simulation environment. The simulation results show that the proposed control algorithm is capable of improving vehicle handling stability and maintaining vehicle yaw stability.

Passive fault-tolerant path following control of autonomous distributed drive electric vehicle considering steering system fault

Abstract In the path following process, once vehicle steering system fails, the common path following control system will not work properly, and even worse, the vehicle will be seriously deviated from the ideal path and the risk of vehicle instability will also increase. Reliable fault-tolerant control strategy can promote the autonomous vehicle to maintain stability and path following accuracy in case of failure. In this paper, a passive fault-tolerant path following control method of autonomous distributed drive electric vehicle is presented considering the vehicle steering system fault. The reduced-order Kalman filter is applied to estimate the vehicle sideslip angle and the vehicle steering system fault. The hierarchical control strategy was developed, and in the upper layer controller, the adaptive sliding mode control method is proposed to facilitate the fault-tolerant path following controller and used to improve the lateral stability and anti-roll performance of vehicle and ensure path following accuracy at the same time, using the estimated sideslip angle and steering system fault as inputs. In the lower layer controller, a novel adaptive orientated tire force allocation method is proposed to execute the control efforts of upper layer controller. The simulations are implemented in the CarSim-Simulink co-simulation platform, and the effectiveness of proposed fault-tolerant path following control method is verified.

Estimation of vehicle sideslip angle scheme using finite-time convergence algorithm

Since vehicle sideslip angle estimation scheme is a real-time application, in essence, the scheme's convergence speed is an issue worth attention. This paper presents a new estimator scheme whose output is theoretically guaranteed to converge to real value in the desired interval, and this makes it possible to be a more reasonable solution for application such as electronic stabilisation control (ESC). To improve the accuracy and adaptive capability of this scheme, the unmodelled error compensating mechanism is adopted. Then experiment results based on veDYNA vehicle dynamic simulation environment validate the applicability of the method.

Direct yaw control based on a phase plan decomposition for enhanced vehicle stability

This paper introduces an advanced direct yaw control (DYC) by supervision with the aim of improving the safety of vehicles. The proposed DYC is based on a hierarchical approach and a global stabilizing yaw moment is calculated by combining two different controllers in order to control yaw rate and vehicle sideslip angle. The activation of each controller depends on the critical driving situation detected by the proposed supervisor. The latter is based on a yaw rate - sideslip angle phase plan decomposition by using the limits of the yaw motion variables. Finally, the global stabilizing yaw moment will be distributed on the four wheels through the control allocation by using differential braking.

Integrated state and parameter estimation for vehicle dynamics control

Most modern day automotive chassis control systems employ a feedback control structure. Therefore, a real-time estimate of the vehicle handling dynamic states and tyre-road contact parameters are invaluable for enhancing the performance of current vehicle control systems, such as anti-lock brake system (ABS) and electronic stability program (ESP). Today's production cars are equipped with onboard sensors (e.g., a 3-axis accelerometer, 3-axis gyroscope, steering wheel angle sensor, and wheel speed sensors) which when used in conjunction with certain model based observers can be used to identify relevant vehicle states for optimal control of comfort, stability and handling. However, some key variables such as the tyre forces, road bank/grade angles, and the tyre-road friction coefficient, which have a significant impact on vehicle handling performance and safety are difficult to measure using sensors already onboard vehicles. This paper introduces an integrated vehicle state estimator comprising a series of model-based and kinematic-based observers for estimating these unmeasurable states. Using an appropriate vehicle model, kinematic equations of motion and vehicle sensor data, the unknown vehicle states as well as the tyre-road contact forces are estimated by implementing a series of observers arranged in a cascade structure. Key estimated signals include the vehicle side slip angle (β), tyre longitudinal/lateral/vertical forces, and the tyre-road friction coefficient (μ). The performance of the proposed estimators has been evaluated via computer simulations conducted using the vehicle dynamics software CarSim®. An effectively designed merging scheme ensures robust estimation performance even during the vehicle manoeuvres which show highly nonlinear tyre characteristics and in the existence of road inclination or bank angle.

Estimation of vehicle sideslip angle scheme using finite-time convergence algorithm

Estimation of vehicle sideslip angle scheme using finite-time convergence algorithm

Estimation of Road Bank Angle and Vehicle Side Slip Angle Using Bayesian Tracking and Kalman Filter Approach

A lateral acceleration is considered to be a significant sensor signal for an estimation of a side slip angle. Due to the fact that a characteristic of a lateral G sensor, the sensor has a technical issue when a road bank angle has presented. In order to resolve the issue, this paper describes a novel method for the real time estimation of a vehicle side slip angle and a road bank angle simultaneously. A Bayesian tracking approach is used to estimate the road bank angle by comparing a measured lateral acceleration with the calculated one in the case of various angle. A Kalman Filter has been implemented through bicycle model using vehicle roll angle, road bank angle and angular velocity of side slip angle. The performance of the proposed estimation method has been evaluated via vehicle tests on a real road.

Vehicle Sideslip Angle and Road Friction Estimation Using Online Gradient Descent Algorithm

Estimating vehicle sideslip angle and road friction in real time is of great significance for vehicle stability control and intelligent vehicle lateral control. These parameters are often difficult to obtain directly and the high cost of measuring instruments restricts their application in general vehicle control. Therefore, an estimation method based on online gradient descent (OGD) algorithm for vehicle sideslip angle and road friction is proposed. For the front-wheel-steer and front-wheel-drive vehicle, the vehicle's lateral dynamics model is established with smaller assumptions. And an unknown input observer is designed to estimate the tire's lateral force of the rear wheel. On the basis of this, the parameter estimation is transformed into the parameter optimization problem and the cost function is designed by using the nonlinear tire model, i.e., magic formula, and its gradient formula. Then, the OGD algorithm is used to estimate the sideslip angle and road friction, respectively. The effectiveness of the proposed method is evaluated via numerical simulation based on MATLAB/Simulink and CarSim software platform. The results show that the method can reliably and accurately estimate the vehicle sideslip angle and the road friction under a variety of test conditions. The proposed algorithm can effectively suppress the influences of sensor noise, longitudinal velocity change, and tire force nonlinearity on the estimation results.

Disturbance Observer-Based Sideslip Angle Control for Improving Cornering Characteristics of In-Wheel Motor Electric Vehicles

In this paper, a robust sideslip angle controller based on the direct yaw moment control (DYC) is proposed for in-wheel motor electric vehicles. Many studies have demonstrated that the DYC is one of the effective methods to improve vehicle maneuverability and stability. Previous approaches to achieve the DYC used differential braking and active steering system. Not only that, the conventional control systems were commonly dependent on the feedback of the yaw rate. In contrast to the traditional control schemes, however, this paper proposes a novel approach based on sideslip angle feedback without controlling the yaw rate. This is mainly because if the vehicle sideslip angle is controlled properly, the intended sideslip angle helps the vehicle to pass through the corner even at high speed. On the other hand, the vehicle may become unstable because of the too large sideslip caused by unexpected yaw disturbances and model uncertainties of time-varying parameters. From this aspect, disturbance observer (DOB) is employed to assure robust performance of the controller. The proposed controller was realized in CarSim model described actual electric vehicle and verified through computer simulations.

Direct‐yaw‐moment control of four‐wheel‐drive electrical vehicle based on lateral tyre–road forces and sideslip angle observer

Considering some technical and economic reasons, it is not easy to directly measure the vehicular moving parameters (such as tyre-road forces and vehicle sideslip angle) in electronic stability programme systems. This study proposes a method to estimate lateral tyre-road forces and vehicle sideslip angle by utilising real-time measurements, based on the unscented Kalman filter. Direct-yaw-moment control can effectively guarantee the stability of vehicle while steering at a high speed. This study proposed a hierarchical control strategy as the solution to the problem of the yaw-moment distribution. The overloop controller is designed to calculate the desired yaw moment based on the estimated lateral tyre-road forces and sideslip angle, using the sliding mode control. The servo-loop controller is designed to optimise the torque distribution using weighted-least-squares method based on the desired yaw moment obtained from the overloop controller. MATLAB/Simulink with Carsim is applied for the simulation experiment, the results demonstrate the effectiveness of the lateral tyre-road force and sideslip angle observer, and the optimal allocation controller could improve the handling stability and energy efficiency dramatically.

Lateral dynamics of a SUV on deformable surfaces by system identification. Part I. Identification experiment

The paper presents a study on lateral dynamics of a 1.6 tonne Sport Utility Vehicle SUV on deformable surfaces performed by means of system identification method. The first part of this study describes an identification experiment, methods and procedures. The identification experiment, in which steering wheel rotation was an input and vehicle motion in the lateral direction was an output has been conducted on three different surfaces: a loess and a sandy soil and on wet snow. The vehicle used for the experiment was equipped with a steering robot to apply repeatable excitations and a high precision Digital Global Positioning System DGPS system to gather dynamic response of the test vehicle, physical measures of the resulting motion: lateral acceleration, yaw rate and vehicle side slip angle. The vehicle was driven with a constant speed of 10km/h. The steering robot input sine wave excitation at 0.5, 1.0 and 2.5 Hz, as well as ramp change (or trapezoidal) excitation with steering wheel rate of 100, 500 and 1500deg/s. It was concluded the methods applied in the field tests were informative and in the sense of the system identification method.